Abstract:
:Many data sets one could use for population genetics contain artifactual sites, i.e., sequencing errors. Here, we first explore the impact of such errors on several common summary statistics, assuming that sequencing errors are mostly singletons. We thus show that in the presence of those errors, estimators of can be strongly biased. We further show that even with a moderate number of sequencing errors, neutrality tests based on the frequency spectrum reject neutrality. This implies that analyses of data sets with such errors will systematically lead to wrong inferences of evolutionary scenarios. To avoid to these errors, we propose two new estimators of theta that ignore singletons as well as two new tests Y and Y* that can be used to test neutrality despite sequencing errors. All in all, we show that even though singletons are ignored, these new tests show some power to detect deviations from a standard neutral model. We therefore advise the use of these new tests to strengthen conclusions in suspicious data sets.
journal_name
Geneticsjournal_title
Geneticsauthors
Achaz Gdoi
10.1534/genetics.107.082198subject
Has Abstractpub_date
2008-07-01 00:00:00pages
1409-24issue
3eissn
0016-6731issn
1943-2631pii
genetics.107.082198journal_volume
179pub_type
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